Cleaned Datasets and Analysis Scripts for EVs Charging stations and Grid Impact in Egypt
Description
This dataset contains cleaned and processed data used in the study of smart electric vehicle (EV) charging stations and their impact on the electrical grid in Egypt. EV charging station data were collected from PlugShare (snapshot on March 15, 2024) and underwent duplicate removal and quality assurance (QA) checks. District-level population projections (2020–2030) were obtained from CAPMAS and Cairo Governorate publications. National electricity load profiles (2019–2024) were derived from the Egyptian Electricity Holding Company (EEHC) and the Ministry of Electricity and Renewable Energy (MOEE) official reports. In addition to the datasets (CSV format), the repository includes analysis scripts for K-means clustering, SPDI/STBI index calculations, and spatial mapping. These resources enable full reproducibility of the study results and can be reused in further research on EV infrastructure planning, demand analysis, and smart grid integration in Egypt and similar contexts.
Files
Steps to reproduce
1. Download the provided cleaned datasets (CSV files). 2. Open the analysis scripts (Python/MATLAB). 3. Run the duplicate removal and quality assurance (QA) script to verify data integrity. 4. Load the EV charging station dataset and apply K-means clustering analysis. 5. Use the provided scripts to calculate SPDI and STBI indices. 6. Run the mapping script to render spatial distributions of charging demand and grid impact. 7. For population data, use the CAPMAS district-level projections (2020–2030) and merge with charging data. 8. For national electricity load profiles (2019–2024), import EEHC and MOEE datasets and combine with clustering results. 9. All results can be reproduced using the provided Jupyter Notebook/MATLAB files without modification.
Institutions
- Helwan University